Senior Machine Learning Engineer

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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Mental health support

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Relocation assistance

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Childcare support

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Senior From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Company

Company stage

Series A From the posting source checked Jun 20, 2026

Application

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Senior Machine Learning Engineer United States Raspberry AI Raspberry AI is a leading provider of industry-defining AI design software for fashion brands and retailers. Our software empowers brands to rapidly understand consumer demand and create unique designs within minutes. Leveraging cutting-edge AI analytics and generative AI capabilities, we help fashion brands revolutionize their design and merchandising processes. We are a Series A startup, backed by top-tier venture capital firms such as Andreessen Horowitz, Khosla Ventures, MVP and Greycroft. About the Role This is a full-time remote role for a Senior Machine Learning Engineer at Raspberry AI. We are seeking a highly talented and motivated Machine Learning Engineer to join our growing ML team. In this role, you will focus on improving the quality and performance of our cutting-edge diffusion models, pushing the boundaries of generative AI in the fashion domain. Additional responsibilities may be assigned as business needs evolve. Responsibilities - Conduct applied research and experimentation on state-of-the-art diffusion model architectures and training techniques. - Implement and evaluate novel techniques for improving quality and controllability in generated designs. - Analyze and interpret experimental results, draw meaningful conclusions, and communicate findings effectively. - Collaborate closely with the team to translate prototypes into production-ready systems. - Stay abreast of the latest advancements in diffusion models, deep learning, and generative AI research. Requirements - Master's or Ph.D. in Computer Science, Machine Learning, or a related field. 3+ years of industry experience. - Strong theoretical and practical understanding of deep learning, with a focus

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